{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "MAX_SEQUENCE_LENGTH = 1400 # 句子 上限1400个词\n",
    "EMBEDDING_DIM = 100 # 100d 词向量"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 数据集\n",
    "HTTP DATASET CSIC 2010: http://www.isi.csic.es/dataset/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "36000 36000 31020\n"
     ]
    }
   ],
   "source": [
    "# 获取数据集\n",
    "# GET 以 Connection + /n + /n 结尾\n",
    "# POST 以 Content-Length + /n + params + /n 结尾\n",
    "\n",
    "def read_data(path):\n",
    "    data = []\n",
    "    labels = []\n",
    "    with open(path) as f:\n",
    "        while True:\n",
    "            line = f.readline()\n",
    "            content = line\n",
    "            if line == '': break \n",
    "            if line[:3] == 'GET':\n",
    "                while True:\n",
    "                    line = f.readline()\n",
    "                    if line[:10] == 'Connection': break\n",
    "                    else: content += line\n",
    "                f.readline() # none\n",
    "                f.readline() # none\n",
    "            elif line[:4] == 'POST':\n",
    "                while True:\n",
    "                    line = f.readline()\n",
    "                    if line[:14] == 'Content-Length': break\n",
    "                    else: content += line\n",
    "                f.readline() # none\n",
    "                content += f.readline()\n",
    "                f.readline() # none\n",
    "            data.append(content)\n",
    "    return data\n",
    "\n",
    "data1 = 'data/normalTrafficTest.txt'\n",
    "data2 = 'data/normalTrafficTraining.txt'\n",
    "data3 = 'data/anomalousTrafficTest.txt'\n",
    "X1 = read_data(data1)\n",
    "X2 = read_data(data2)\n",
    "X3 = read_data(data3)\n",
    "print(len(X1), len(X2), len(X3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "103020 103020\n"
     ]
    }
   ],
   "source": [
    "data = []\n",
    "labels = []\n",
    "data.extend(X1)\n",
    "labels.extend([1] * len(X1))\n",
    "data.extend(X2)\n",
    "labels.extend([1] * len(X2))\n",
    "data.extend(X3)\n",
    "labels.extend([0] * len(X3))\n",
    "print(len(data), len(labels))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'GET http://localhost:8080/tienda1/index.jsp HTTP/1.1\\nUser-Agent: Mozilla/5.0 (compatible; Konqueror/3.5; Linux) KHTML/3.5.8 (like Gecko)\\nPragma: no-cache\\nCache-control: no-cache\\nAccept: text/xml,application/xml,application/xhtml+xml,text/html;q=0.9,text/plain;q=0.8,image/png,*/*;q=0.5\\nAccept-Encoding: x-gzip, x-deflate, gzip, deflate\\nAccept-Charset: utf-8, utf-8;q=0.5, *;q=0.5\\nAccept-Language: en\\nHost: localhost:8080\\nCookie: JSESSIONID=EA414B3E327DED6875848530C864BD8F\\n'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'POST http://localhost:8080/tienda1/publico/anadir.jsp HTTP/1.1\\nUser-Agent: Mozilla/5.0 (compatible; Konqueror/3.5; Linux) KHTML/3.5.8 (like Gecko)\\nPragma: no-cache\\nCache-control: no-cache\\nAccept: text/xml,application/xml,application/xhtml+xml,text/html;q=0.9,text/plain;q=0.8,image/png,*/*;q=0.5\\nAccept-Encoding: x-gzip, x-deflate, gzip, deflate\\nAccept-Charset: utf-8, utf-8;q=0.5, *;q=0.5\\nAccept-Language: en\\nHost: localhost:8080\\nCookie: JSESSIONID=788887A0F479749C4CEEA1E268B4A501\\nContent-Type: application/x-www-form-urlencoded\\nConnection: close\\nid=1&nombre=Jam%F3n+Ib%E9rico&precio=39&cantidad=41&B1=A%F1adir+al+carrito\\n'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 字向量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ubuntu/anaconda3/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
      "  from ._conv import register_converters as _register_converters\n",
      "Using TensorFlow backend.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 80 unique tokens.\n",
      "Shape of data tensor: (103020, 1400)\n"
     ]
    }
   ],
   "source": [
    "# https://keras-cn-docs.readthedocs.io/zh_CN/latest/blog/word_embedding/\n",
    "import numpy as np\n",
    "from keras.preprocessing.text import Tokenizer\n",
    "from keras.preprocessing.sequence import pad_sequences\n",
    "\n",
    "# tokenizer\n",
    "texts = data\n",
    "tokenizer = Tokenizer(char_level=True)\n",
    "tokenizer.fit_on_texts(texts)\n",
    "word_index = tokenizer.word_index\n",
    "\n",
    "# sequences\n",
    "sequences = tokenizer.texts_to_sequences(data)\n",
    "\n",
    "# padding\n",
    "data = pad_sequences(sequences, maxlen=MAX_SEQUENCE_LENGTH)\n",
    "\n",
    "print('Found %s unique tokens.' % len(word_index))\n",
    "print('Shape of data tensor:', data.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "\n",
    "token_path = 'model/tokenizer.pkl'\n",
    "pickle.dump(tokenizer, open(token_path, 'wb'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "import random\n",
    "\n",
    "# 打乱顺序\n",
    "index = [i for i in range(len(data))]\n",
    "random.shuffle(index)\n",
    "data = np.array(data)[index]\n",
    "labels = np.array(labels)[index]\n",
    "\n",
    "TRAIN_SPLIT = 0.8 # 20% 测试集\n",
    "TRAIN_SIZE = int(len(data) * TRAIN_SPLIT)\n",
    "\n",
    "X_train, X_test = data[0:TRAIN_SIZE], data[TRAIN_SIZE:]\n",
    "Y_train, Y_test = labels[0:TRAIN_SIZE], labels[TRAIN_SIZE:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train len: 82416\n",
      "test len: 20604\n"
     ]
    }
   ],
   "source": [
    "print('train len:', len(X_train))\n",
    "print('test len:', len(X_test))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 训练"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "from keras import backend as K\n",
    "\n",
    "import os\n",
    "os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"1\"\n",
    "\n",
    "G = 1 # GPU 数量\n",
    "gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=0.8)\n",
    "session = tf.Session(config=tf.ConfigProto(gpu_options=gpu_options, allow_soft_placement=True))\n",
    "K.set_session(session)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Bi-LSTM + CNN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "embedding_1 (Embedding)      (None, 1400, 100)         8100      \n",
      "_________________________________________________________________\n",
      "bidirectional_1 (Bidirection (None, 1400, 128)         84480     \n",
      "_________________________________________________________________\n",
      "conv1d_1 (Conv1D)            (None, 1398, 128)         49280     \n",
      "_________________________________________________________________\n",
      "batch_normalization_1 (Batch (None, 1398, 128)         512       \n",
      "_________________________________________________________________\n",
      "activation_1 (Activation)    (None, 1398, 128)         0         \n",
      "_________________________________________________________________\n",
      "max_pooling1d_1 (MaxPooling1 (None, 349, 128)          0         \n",
      "_________________________________________________________________\n",
      "flatten_1 (Flatten)          (None, 44672)             0         \n",
      "_________________________________________________________________\n",
      "dense_1 (Dense)              (None, 64)                2859072   \n",
      "_________________________________________________________________\n",
      "batch_normalization_2 (Batch (None, 64)                256       \n",
      "_________________________________________________________________\n",
      "activation_2 (Activation)    (None, 64)                0         \n",
      "_________________________________________________________________\n",
      "dense_2 (Dense)              (None, 1)                 65        \n",
      "_________________________________________________________________\n",
      "batch_normalization_3 (Batch (None, 1)                 4         \n",
      "_________________________________________________________________\n",
      "activation_3 (Activation)    (None, 1)                 0         \n",
      "=================================================================\n",
      "Total params: 3,001,769\n",
      "Trainable params: 3,001,383\n",
      "Non-trainable params: 386\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "from keras.models import Sequential\n",
    "from keras.layers import Activation, BatchNormalization, Flatten\n",
    "from keras.layers import Dense, LSTM, Convolution1D, MaxPooling1D\n",
    "from keras.layers.embeddings import Embedding\n",
    "from keras.layers.wrappers import Bidirectional\n",
    "\n",
    "QA_EMBED_SIZE = 64\n",
    "DROPOUT_RATE = 0.3\n",
    "\n",
    "model = Sequential()\n",
    "model.add(Embedding(len(word_index) + 1, EMBEDDING_DIM, input_length=MAX_SEQUENCE_LENGTH))\n",
    "model.add(Bidirectional(LSTM(QA_EMBED_SIZE, return_sequences=True, dropout=DROPOUT_RATE, recurrent_dropout=DROPOUT_RATE)))\n",
    "model.add(Convolution1D(filters=128, kernel_size=3, padding='valid', activation='relu'))\n",
    "model.add(BatchNormalization())\n",
    "model.add(Activation('relu'))\n",
    "model.add(MaxPooling1D(4))\n",
    "model.add(Flatten())\n",
    "\n",
    "model.add(Dense(QA_EMBED_SIZE))\n",
    "model.add(BatchNormalization())\n",
    "model.add(Activation('relu'))\n",
    "model.add(Dense(1))\n",
    "model.add(BatchNormalization())\n",
    "model.add(Activation(\"sigmoid\"))\n",
    "\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 模型可视化 https://keras-cn.readthedocs.io/en/latest/other/visualization/\n",
    "from keras.utils import plot_model\n",
    "from IPython import display\n",
    "\n",
    "# pip install pydot-ng\n",
    "# sudo apt-get install graphviz\n",
    "plot_model(model, to_file=\"img/model-blstm-cnn.png\", show_shapes=True)\n",
    "display.Image('img/model-blstm-cnn.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train on 57691 samples, validate on 24725 samples\n",
      "Epoch 1/5\n",
      "57691/57691 [==============================] - 4365s 76ms/step - loss: 0.3185 - acc: 0.9044 - precision: 0.9339 - recall: 0.9290 - f1: 0.9300 - val_loss: 0.2169 - val_acc: 0.9691 - val_precision: 0.9725 - val_recall: 0.9832 - val_f1: 0.9776\n",
      "Epoch 2/5\n",
      "57691/57691 [==============================] - 4323s 75ms/step - loss: 0.1366 - acc: 0.9785 - precision: 0.9774 - recall: 0.9923 - f1: 0.9846 - val_loss: 0.0983 - val_acc: 0.9840 - val_precision: 0.9796 - val_recall: 0.9975 - val_f1: 0.9884\n",
      "Epoch 3/5\n",
      "57691/57691 [==============================] - 4473s 78ms/step - loss: 0.0832 - acc: 0.9865 - precision: 0.9849 - recall: 0.9959 - f1: 0.9902 - val_loss: 0.0637 - val_acc: 0.9884 - val_precision: 0.9847 - val_recall: 0.9986 - val_f1: 0.9915\n",
      "Epoch 4/5\n",
      "57691/57691 [==============================] - 4417s 77ms/step - loss: 0.0587 - acc: 0.9897 - precision: 0.9882 - recall: 0.9971 - f1: 0.9925 - val_loss: 0.0566 - val_acc: 0.9893 - val_precision: 0.9854 - val_recall: 0.9993 - val_f1: 0.9922\n",
      "Epoch 5/5\n",
      "57691/57691 [==============================] - 4454s 77ms/step - loss: 0.0414 - acc: 0.9925 - precision: 0.9914 - recall: 0.9979 - f1: 0.9946 - val_loss: 0.0370 - val_acc: 0.9917 - val_precision: 0.9915 - val_recall: 0.9965 - val_f1: 0.9939\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7efe673bfe10>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from keras.callbacks import EarlyStopping, ModelCheckpoint, TensorBoard\n",
    "# from keras.utils import multi_gpu_model\n",
    "from evaluate import *\n",
    "\n",
    "EPOCHS = 5\n",
    "BATCH_SIZE = 64 * G\n",
    "VALIDATION_SPLIT = 0.3 # 30% 验证集\n",
    "\n",
    "early_stopping = EarlyStopping(monitor='val_loss', patience=10)\n",
    "model_checkpoint = ModelCheckpoint('model/model-blstm-cnn.h5', save_best_only=True, save_weights_only=True)\n",
    "tensor_board = TensorBoard('log/tflog-blstm-cnn', write_graph=True, write_images=True)\n",
    "\n",
    "# model = multi_gpu_model(model)\n",
    "\n",
    "model.compile(loss='binary_crossentropy',\n",
    "                  optimizer='adam',\n",
    "                  metrics=['accuracy', precision, recall, f1])\n",
    "\n",
    "model.fit(X_train, Y_train, epochs=EPOCHS, batch_size=BATCH_SIZE, \n",
    "          validation_split=VALIDATION_SPLIT, shuffle=True, \n",
    "          callbacks=[early_stopping, model_checkpoint, tensor_board])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "20604/20604 [==============================] - 292s 14ms/step\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[0.038126186209337914,\n",
       " 0.9911667637351971,\n",
       " 0.9906120255858522,\n",
       " 0.9968340528795868,\n",
       " 0.9936446852879347]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.evaluate(X_test, Y_test, verbose=1, batch_size=BATCH_SIZE)"
   ]
  }
 ],
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